Demand estimation of water resources based on algorithm comparison Online publication date: Fri, 12-Apr-2019
by Junyan Wang; Jiangjiang Zhang; Xingjuan Cai; Yanyan Ma
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 16, No. 2, 2019
Abstract: Water is the source of life and the correct assessment of water resources is an important pre-requisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013-2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms.
Online publication date: Fri, 12-Apr-2019
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